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Home/ Questions/Q 5841711
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Editorial Team
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Editorial Team
Asked: May 22, 20262026-05-22T11:55:29+00:00 2026-05-22T11:55:29+00:00

I’m writing a genetic algorithm to generate the string helloworld. But the evolve function

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I’m writing a genetic algorithm to generate the string “helloworld”. But the evolve function creates a stack overflow when n is 10,000 or more.

module Genetics where

import Data.List (sortBy)
import Random (randomRIO)
import Control.Monad (foldM)

class Gene g where
    -- How ideal is the gene from 0.0 to 1.0?
    fitness :: g -> Float

    -- How does a gene mutate?
    mutate :: g -> IO g

    -- How many species will be explored?
    species :: [g] -> Int

orderFitness :: (Gene g) => [g] -> [g]
orderFitness = reverse . sortBy (\a b -> compare (fitness a) (fitness b))

compete :: (Gene g) => [g] -> IO [g]
compete pool = do
    let s = species pool
    variants <- (mapM (mapM mutate) . map (replicate s)) pool
    let pool' = (map head . map orderFitness) variants
    return pool'

evolve :: (Gene g) => Int -> [g] -> IO [g]
evolve 0 pool = return pool
evolve n pool = do
    pool' <- compete pool
    evolve (n - 1) pool'

With species pool = 8, a pool of 8 genes replicates to 8 groups. Each group mutates, and the fittest of each group is selected for further evolution (back to 8 genes).

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1 Answer

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  1. Editorial Team
    Editorial Team
    2026-05-22T11:55:30+00:00Added an answer on May 22, 2026 at 11:55 am

    Thanks to Don’s deepseq suggestion, I was able to narrow the problem to mapM mutate which made too many thunks. The new version has mutate', which uses seq to prevent thunking.

    module Genetics where
    
    import Data.List (maximumBy)
    import Random (randomRIO)
    
    class Gene g where
        -- How ideal is the gene from 0.0 to 1.0?
        fitness :: g -> Float
    
        -- How does a gene mutate?
        mutate :: g -> IO g
    
        -- How many species will be explored in each round?
        species :: [g] -> Int
    
    best :: (Gene g) => [g] -> g
    best = maximumBy (\a b -> compare (fitness a) (fitness b))
    
    -- Prevents stack overflow
    mutate' :: (Gene g) => g -> IO g
    mutate' gene = do
        gene' <- mutate gene
        gene' `seq` return gene'
    
    drift :: (Gene g) => [[g]] -> IO [[g]]
    drift = mapM (mapM mutate')
    
    compete :: (Gene g) => [g] -> IO [g]
    compete pool = do
        let islands = map (replicate (species pool)) pool
        islands' <- drift islands
        let representatives = map best islands'
        return representatives
    
    evolve :: (Gene g) => Int -> [g] -> IO [g]
    evolve 0 pool = return pool
    evolve n pool = compete pool >>= evolve (n - 1)
    

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